NTIRE 2021 Challenge on Video Super-Resolution

• Main Authors: Son, Sanghyun, Lee, Suyoung, Nah, Seungjun, Timofte, Radu, Lee, Kyoung Mu, Chan, Kelvin C. K., Zhou, Shangchen, Xu, Xiangyu, Loy, Chen Change, Jiang, Boyuan, Lin, Chuming, Dong, Yuchun, Luo, Donghao, Chu, Wenqing, Tai, Ying, Wang, Chengjie, Li, Jilin, Chen, Chengpeng, Lu, Xin, Chen, Liangyu, Lin, Jing, Du, Guodong, Hao, Jia, Zou, Xueyi, Zhang, Qi, Jiang, Lielin, Li, Xin, Liu, Fanglong, He, Dongliang, Li, Fu, Yi, Peng, Wang, Zhongyuan, Jiang, Kui, Jiang, Junjun, Ma, Jiayi, Chen, Yuxiang, Wang, Yutong, Liu, Ting, Sun, Qichao, Liang, Huanwei, Li, Yiming, Li, Zekun, Shang, Fanjie, Guo, Chen, Li, Haining, Luo, Renjun, Shen, Longjie, Zafirouli, Kassiani, Konstantoudakis, Konstantinos, Daras, Petros, Song, Xiaowei, Zhuo, Xu, Liu, Hanxi, Guo, Mengxi, Li, Junlin, Li, Yu, Zhu, Ye, Wang, Qing, Zhao, Shijie, Sun, Xiaopeng, Zhan, Gen, Xie, Tangxin, Jia, Yu, Lu, Yunhua, Sun, Mengdi, Michelini, Pablo Navarrete, Zhang, Xueheng, Jiang, Hao, Chen, Zhiyu, Chen, Li, Xiong, Zhiwei, Xiao, Zeyu, Xu, Ruikang, Cheng, Zhen, Fu, Xueyang, Song, Fenglong, Luo, Zhipeng, Yao, Yuehan, Shah, Nisarg A., Dipta Das, Sourya, Zhao, Peng, Shi, Yukai, Liu, Hongying, Shang, Fanhua, Liu, Yuanyuan, Chen, Fei, Yu, Fangxu, Gao, Ruisheng, Bai, Yixin, Heo, Jeonghwan, Yue, Shijie, Li, Chenghua, Li, Jinjing, Gang, Ruipeng, Wee, Seungwoo, Jeong, Jechang, Li, Chen, Wen, Geyingjie, Chai, Xinning, Song, Li
• Format: Conference Proceeding
• Language: English
• Subjects: Casting; Computer vision; Conferences; Focusing; Image restoration; Pattern recognition; Superresolution
• ISSN: 2160-7516
• DOI: 10.1109/CVPRW53098.2021.00026

Super-Resolution (SR) is a fundamental computer vision task that aims to obtain a high-resolution clean image from the given low-resolution counterpart. This paper reviews the NTIRE 2021 Challenge on Video Super-Resolution. We present evaluation results from two competition tracks as well as the proposed solutions. Track 1 aims to develop conventional video SR methods focusing on the restoration quality. Track 2 assumes a more challenging environment with lower frame rates, casting spatio-temporal SR problem. In each competition, 247 and 223 participants have registered, respectively. During the final testing phase, 14 teams competed in each track to achieve state-of-the-art performance on video SR tasks.